Optimization and correlations development for heat transfer and fluid flow characteristics of ZnO/H₂O-ethylene glycol-based nanofluid flow through an inclined ribbed square duct

References

• H. E. Ahmed, M. I. Ahmed, and M. Z. Yusoff, “Numerical and experimental comparative study on nanofluids flow and heat transfer in a ribbed triangular duct,” Exp. Heat Transf., vol. 29, no. 6, pp. 759–780, 2016. DOI: 10.1080/08916152.2015.1113216.
   Web of Science ®Google Scholar
• F. Ltarazi et al., “Analysis and implementation of thermal heat exchanger tube performance with helically pierced twisted tape inserts using ANFIS model,” Math. Prob. Eng., vol. 2021, pp. 1–13, 2021. DOI: 10.1155/2021/1734909.
   Web of Science ®Google Scholar
• S. Eiamsa-Ard and K. Wongcharee, “Experimental study of TiO2-water nanofluid flow in corrugated tubes mounted with semi-circular wing tapes,” Heat Transf. Eng., vol. 39, no. 1, pp. 1–14, 2018. DOI: 10.1080/01457632.2017.1280277.3.
   Web of Science ®Google Scholar
• S. Kumar, S. K. Gautam, A. Kumar, R. Maithani, and A. Kumar, “Sustainability assessment of different nanoparticle for heat exchanger applications: An intuitionistic fuzzy combinative distance-based assessment method,” Acta Innov., vol. 40, no. 40, pp. 44–63, 2021. DOI: 10.32933/ActaInnovations.40.4.
   Google Scholar
• H. E. Ahmed and M. Z. Yusoff, “Impact of delta-winglet pair of vortex generators on the thermal and hydraulic performance of a triangular channel using Al2O3-water nanofluid,” J. Heat Transf., vol. 136, pp. 1901–1909, 2014. DOI: 10.1115/1.4025434.
   Web of Science ®Google Scholar
• A. N. Al-Shamani et al., “Enhancement heat transfer characteristics in the channel with Trapezoidal rib-groove using nanofluids,” Case Stud. Therm. Eng., vol. 5, pp. 48–58, 2015. DOI: 10.1016/j.csite.2014.12.003.
   Web of Science ®Google Scholar
• H. Z. Han, B. X. Li, H. Wu, and W. Shao, “Multi-objective shape optimization of double pipe heat exchanger with inner corrugated tube using RSM method,” Int. J. Therm. Sci., vol. 90, pp. 173–186, 2015. DOI: 10.1016/j.ijthermalsci.2014.12.010.
   Web of Science ®Google Scholar
• D. Mansoury, F. I. Doshmanziari, S. Rezaie, and M. M. Rashidi, “Effect of Al2O3/water nanofluid on performance of parallel flow heat exchangers: An experimental approach,” J. Therm. Anal. Calorim., vol. 135, no. 1, pp. 625–643, 2019. DOI: 10.1007/s10973-018-7286-8.
   Web of Science ®Google Scholar
• S. Kumar, A. D. Kothiyal, M. S. Bisht, and A. Kumar, “Effect of nanofluid flow and protrusion ribs on performance in square channels: An experimental investigation,” J. Enh. Heat Transf., vol. 26, no. 1, pp. 75–100, 2019. DOI: 10.1615/JEnhHeatTransf.2018026042.
   Web of Science ®Google Scholar
• S. V. Mahmoodi-Jezeh and B. C. Wang, “Direct numerical simulation of turbulent heat transfer in a square duct with transverse ribs mounted on one wall,” Int. J. Heat Fluid Flow, vol. 89, pp. 108782, 2021. DOI: 10.1016/j.ijheatfluidflow.2021.108782.
   Web of Science ®Google Scholar
• C. Yan, J. Xu, S. Wang, and G. Liu, “Numerical study of convective heat transfer to supercritical CO2 in vertical heated tubes,” Int. Commun. Heat Mass Transf., vol. 137, pp. 106242, 2022. DOI: 10.1016/j.icheatmasstransfer.2022.106242.
   Web of Science ®Google Scholar
• J. Hasnain and N. Abid, “Numerical investigation for thermal growth in water and engine oil-based ternary nanofluid using three different shaped nanoparticles over a linear and nonlinear stretching sheet,” Numer. Heat Transf. A Appl., 2022. DOI: 10.1080/10407782.2022.2104582.
   Web of Science ®Google Scholar
• M. G. P. Kumar, B. G. Rao, B. Sreenivasulu, and S. S. Arasavelli, “Effect of vibration on heat transfer to laminar non-Newtonian nanofluid flowing through a circular pipe: A numerical analysis,” Numer. Heat Transf. A Appl., vol. 82, no. 11, pp. 683–699, 2022. DOI: 10.1080/10407782.2022.2083862.
   Web of Science ®Google Scholar
• M. Gamal, M. S. Radwan, I. G. Elgizawy, and M. H. Shedid, “Heat transfer performance and exergy analyses of MgO and ZnO nanofluids using water/ethylene glycol mixture as base fluid,” Numer. Heat Transf. A Appl., vol. 80, no. 12, pp. 597–616, 2021. DOI: 10.1080/10407782.2021.1962631.
   Web of Science ®Google Scholar
• A. Karimipour, S. A. Bagherzadeh, A. Taghipour, A. Abdollahi, and M. R. Safaei, “A novel nonlinear regression model of SVR as a substitute for ANN to predict conductivity of MWCNT-CuO/water hybrid nanofluid based on empirical data,” Phys. A, vol. 521, pp. 89–97, 2019. DOI: 10.1016/j.physa.2019.01.055.
   Web of Science ®Google Scholar
• S. A. Bagherzadeh, A. D. Orazio, A. Karimipour, M. Goodarzi, and Q. V. Bach, “A novel sensitivity analysis model of EANN for F-MWCNTs–Fe3O4/EG nanofluid thermal conductivity: Outputs predicted analytically instead of numerically to more accuracy and less costs,” Phys. A, vol. 521, pp. 406–415, 2019. DOI: 10.1016/j.physa.2019.01.048.
   Web of Science ®Google Scholar
• M. H. Ahmadi et al., “Comparing various machine learning approaches in modeling the dynamic viscosity of CuO/water nanofluid,” J. Therm. Anal. Calorim., vol. 139, no. 4, pp. 2585–2599, 2020. DOI: 10.1007/s10973-019-08762-z.
   Web of Science ®Google Scholar
• S. O. Giwa, M. Sharifpur, M. Goodarzi, H. Alsulami, and J. P. Meyer, “Influence of base fluid, temperature, and concentration on the thermophysical properties of hybrid nanofluids of alumina–ferrofluid: Experimental data, modeling through enhanced ANN, ANFIS, and curve fitting,” J. Therm. Anal. Calorim., vol. 143, no. 6, pp. 4149–4167, 2021. DOI: 10.1007/s10973-020-09372-w.
   Web of Science ®Google Scholar
• Y. Peng et al., “Potential application of Response Surface Methodology (RSM) for the prediction and optimization of thermal conductivity of aqueous CuO (II) nanofluid: A statistical approach and experimental validation,” Phys. A, vol. 554, pp. 124353, 2020. DOI: 10.1016/j.physa.2020.124353.
   Web of Science ®Google Scholar
• A. Moradikazerouni et al., “Assessment of thermal conductivity enhancement of nano-antifreeze containing single-walled carbon nanotubes: Optimal artificial neural network and curve-fitting,” Phys. A, vol. 521, pp. 138–145, 2019. DOI: 10.1016/j.physa.2019.01.051.
   Web of Science ®Google Scholar
• M. Bahrami et al., “Develop 24 dissimilar ANNs by suitable architectures & training algorithms via sensitivity analysis to better statistical presentation: Measure MSEs between targets & ANN for Fe-CuO/Eg-Water nanofluid,” Phys. A, vol. 519, pp. 159–168, 2019. DOI: 10.1016/j.physa.2018.12.031.
   Web of Science ®Google Scholar
• T. Hussein, S. N. Kaziand, and A. Badarudin, “Turbulent heat transfer to separation nanofluid flow in annular concentric pipe,” Int. J. Therm. Sci., vol. 117, pp. 14–25, 2017. DOI: 10.1016/j.ijthermalsci.2017.03.014.
   Web of Science ®Google Scholar
• H. E. Ahmed et al., “Turbulent heat transfer and nanofluid flow in a triangular duct with vortex generators,” Int. J. Heat Mass Transf., vol. 105, pp. 495–504, 2017. DOI: 10.1016/j.ijheatmasstransfer.2016.10.009.
   Web of Science ®Google Scholar
• K. A. Morteza and S. Mortazavi, “Combined effects of holes and winglets on chevron plate-fins to enhance the performance of a plate-fin heat exchanger working with nanofluid,” Exp. Heat Transf., vol. 32, no. 6, pp. 584–599, 2019. DOI: 10.1080/08916152.2019.1569176.
   Web of Science ®Google Scholar
• Z. Sarbazi and F. Hormozi, “Optimization of thermal and hydraulic performance of nanofluids in a rectangular miniature-channel with various fins using response surface methodology,” J. Therm. Anal. Calorim., vol. 137, no. 3, pp. 711–733, 2019. DOI: 10.1007/s10973-018-7981-5.
   Web of Science ®Google Scholar
• M. Mamourian, K. M. Shirvan, and I. Pop, “Sensitivity analysis for MHD effects and inclination angles on natural convection heat transfer and entropy generation of Al2O3-water nanofluid in square cavity by response surface methodology,” Int. Commun. Heat Mass Transf., vol. 79, pp. 46–57, 2016. DOI: 10.1016/j.icheatmasstransfer.2016.10.001.
   Web of Science ®Google Scholar
• A. Subasi, B. Sahin, and I. Kaymaz, “Multi-objective optimization of a honeycomb heat sink using response surface method,” Int. J. Heat Mass Transf., vol. 101, pp. 295–302, 2016. DOI: 10.1016/j.ijheatmasstransfer.2016.05.012.
   Web of Science ®Google Scholar
• C. Yu, J. Chen, M. Zeng, and B. Gao, “Numerical study on turbulent heat transfer performance of a new parallel-flow shell and tube heat exchanger with sinusoidal wavy tapes using RSM analysis,” Appl. Therm. Eng., vol. 150, pp. 875–887, 2019. DOI: 10.1016/j.applthermaleng.2019.01.043.
   Web of Science ®Google Scholar
• M. Malika and S. S. Sonawane, “Statistical modelling for the Ultrasonic photodegradation of Rhodamine B dye using aqueous based Bi-metal doped TiO2 supported montmorillonite hybrid nanofluid via RSM,” Sustain. Energy Technol. Assess, vol. 44, pp. 100980, 2021. DOI: 10.1016/j.seta.2020.100980.
   Web of Science ®Google Scholar
• I. D. J. Azzawi and A. Aldamook, “Multi-objective optimum design of porous triangular chamber using RSM,” Int. Commun. Heat Mass Transf., vol. 130, pp. 105774, 2022. DOI: 10.1016/j.icheatmasstransfer.2021.105774.
   Web of Science ®Google Scholar
• American Society of Heating Refrigerating and Air-Conditioning Engineers Inc., ASHRAE Handbook - Heating, Ventilating, and Air-Conditioning Applications, Atlanta, USA, pp. 978, 2015.
   Google Scholar
• S. Kumar, M. Shandilya, A. Chauhan, R. Maithani, and A. Kumar, “Experimental analysis of zinc oxide/water/ethylene glycol-based nanofluid in a square duct roughened with inclined ribs,” J. Enh. Heat Transf., vol. 27, no. 8, pp. 687–709, 2020. DOI: 10.1615/JEnhHeatTransf.2020034180.
   Web of Science ®Google Scholar
• C. J. Ho, L. C. Wei, and Z. W. Li, “An experimental investigation of forced convective cooling performance of a microchannel heat sink with Al2O3/water nanofluid,” Appl. Therm. Eng., vol. 30, no. 2–3, pp. 96–103, 2010. DOI: 10.1016/j.applthermaleng.2009.07.003.
   Web of Science ®Google Scholar
• S. J. Kline and F. McClintock, “Describe uncertainties in single sample experiments,” Mech. Eng., vol. 75, pp. 3–8, 1953.
   Google Scholar